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Modeling Spatial Uncertainty for the iPad Pro Depth Sensor

Zea, A. 1; Hanebeck, U. D. 1
1 Institut für Anthropomatik und Robotik (IAR), Karlsruher Institut für Technologie (KIT)

Abstract:

Depth sensors, once exclusively found in research laboratories, are quickly becoming ubiquitous in the mass market. After Apple’s intro-duction of the iPad Pro 2020 with an integrated light detection and ranging (LIDAR) sensor, now even tablets and smartphones are capable of obtaining accurate 3-D information from their environments. This, in turn, increases the reach of applications from technical fields, such as SLAM, object tracking, and object classification, which can now be downloaded on millions of hand-held devices with a couple of taps. This motivates an analysis of the capabilities, strengths, and weaknesses of these depth streams. In this paper, we present a study of the spatial uncertainties of the iPad Pro 2021 depth sensor. First, we describe the hardware used by the device, and provide an overview of the machine learning algorithm that fuses information from the LIDAR sensor with color data to produce a depth image. Then, we analyze the accuracy and precision of the measured depth values, while giving attention to the resulting temporal and spatial correlations. An-other important topic of discussion are the tradeoffs involved in the ex-trapolations that the depth system implements, such as how curvatures change at different distances. ... mehr


Postprint §
DOI: 10.5445/IR/1000159135
Veröffentlicht am 23.03.2026
Scopus
Zitationen: 2
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2022
Sprache Englisch
Identifikator ISSN: 1557-6418
KITopen-ID: 1000159135
Erschienen in Journal of Advances in Information Fusion
Verlag International Society of Information Fusion
Band 17
Heft 2
Seiten 67-77
Nachgewiesen in Scopus
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